A new partial volume segmentation approach to extract bladder wall for computer-aided detection in virtual cystoscopy

Lihong Li; Zigang Wang; Xiang Li; Xinzhou Wei; Howard L. Adler; Wei Huang; Syed A. Rizvi; Hong Meng; Donald P. Harrington M.D.; Zhengrong Liang

doi:10.1117/12.535913

30 April 2004 A new partial volume segmentation approach to extract bladder wall for computer-aided detection in virtual cystoscopy

Lihong Li, Zigang Wang, Xiang Li, Xinzhou Wei, Howard L. Adler, Wei Huang, Syed A. Rizvi, Hong Meng, Donald P. Harrington M.D., Zhengrong Liang

Author Affiliations +

Proceedings Volume 5369, Medical Imaging 2004: Physiology, Function, and Structure from Medical Images; (2004) https://doi.org/10.1117/12.535913
Event: Medical Imaging 2004, 2004, San Diego, California, United States

Abstract

We propose a new partial volume (PV) segmentation scheme to extract bladder wall for computer aided detection (CAD) of bladder lesions using multispectral MR images. Compared with CT images, MR images provide not only a better tissue contrast between bladder wall and bladder lumen, but also the multispectral information. As multispectral images are spatially registered over three-dimensional space, information extracted from them is more valuable than that extracted from each image individually. Furthermore, the intrinsic T₁ and T₂ contrast of the urine against the bladder wall eliminates the invasive air insufflation procedure. Because the earliest stages of bladder lesion growth tend to develop gradually and migrate slowly from the mucosa into the bladder wall, our proposed PV algorithm quantifies images as percentages of tissues inside each voxel. It preserves both morphology and texture information and provides tissue growth tendency in addition to the anatomical structure. Our CAD system utilizes a multi-scan protocol on dual (full and empty of urine) states of the bladder to extract both geometrical and texture information. Moreover, multi-scan of transverse and coronal MR images eliminates motion artifacts. Experimental results indicate that the presented scheme is feasible towards mass screening and lesion detection for virtual cystoscopy (VC).

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Lihong Li, Zigang Wang, Xiang Li, Xinzhou Wei, Howard L. Adler, Wei Huang, Syed A. Rizvi, Hong Meng, Donald P. Harrington M.D., and Zhengrong Liang "A new partial volume segmentation approach to extract bladder wall for computer-aided detection in virtual cystoscopy", Proc. SPIE 5369, Medical Imaging 2004: Physiology, Function, and Structure from Medical Images, (30 April 2004); https://doi.org/10.1117/12.535913

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